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Simulated maximum likelihood estimation of demand systems with corner solutions and panel data application to industrial energy demand
[Estimation par maximum de vraisemblance simulé de systèmes de demande avec solutions en coin et données de panel application à la demande d’énergie industrielle]

Author

Listed:
  • Raja Chakir

    (GREMAQ - Groupe de recherche en économie mathématique et quantitative - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique)

  • Alban Thomas

    (LEERNA - Laboratoire d'Economie de l'Environnement et des Ressources Naturelles - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - INRA - Institut National de la Recherche Agronomique)

Abstract

his paper proposes a convenient method for evaluating energy price elasticities, when firms may switch between energy regimes. The methodology involves estimation of an energy demand system that explicitly deals with the zero expenditures problem, while allowing for unobserved heterogeneity. We apply a Simulated Maximum Likelihood technique for estimating a simultaneous equation energy demand system in the French pulp and paper sector, over the period 1983-1996. Endogenous regime transitions are accounted for when computing energy price elasticities. Our estimates are used to predict the outcome of an environmental policy aimed at reducing CO 2 emissions in the paper and pulp industry.

Suggested Citation

  • Raja Chakir & Alban Thomas, 2003. "Simulated maximum likelihood estimation of demand systems with corner solutions and panel data application to industrial energy demand [Estimation par maximum de vraisemblance simulé de systèmes de demande avec solutions en coin et données de pane," Post-Print hal-05136019, HAL.
    • Handle: RePEc:hal:journl:hal-05136019
    DOI: 10.3917/redp.136.0773
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    2. Lin, Boqiang & Wesseh, Presley K., 2013. "Estimates of inter-fuel substitution possibilities in Chinese chemical industry," Energy Economics, Elsevier, vol. 40(C), pages 560-568.
    3. BEL François & LACROIX Anne & SALANIE François & THOMAS Alban, 2006. "Evaluating the impact of CAP reforms on land use and the environment: a two-step estimation with multiple selection rules and panel data," LERNA Working Papers 06.13.206, LERNA, University of Toulouse.
    4. Wesseh, Presley K. & Lin, Boqiang, 2016. "Factor demand, technical change and inter-fuel substitution in Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 979-991.
    5. Lin, Boqiang & Ahmad, Izhar, 2016. "Energy substitution effect on transport sector of Pakistan based on trans-log production function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1182-1193.
    6. Thomas, Alban & Chakir, Raja, 2020. "Unintended consequences of environmental policies: the case of set-aside and agricultural intensification," TSE Working Papers 20-1066, Toulouse School of Economics (TSE).
    7. Lin, Boqiang & Atsagli, Philip, 2017. "Inter-fuel substitution possibilities in South Africa: A translog production function approach," Energy, Elsevier, vol. 121(C), pages 822-831.
    8. Obafèmi P. Koutchadé & Alain Carpentier & Fabienne Femenia, 2021. "Modeling Corners, Kinks, and Jumps in Crop Acreage Choices: Impacts of the EU Support to Protein Crops," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(4), pages 1502-1524, August.
    9. Lin, Boqiang & Atsagli, Philip & Dogah, Kingsley E., 2016. "Ghanaian energy economy: Inter-production factors and energy substitution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1260-1269.
    10. Wesseh, Presley K. & Lin, Boqiang & Appiah, Michael Owusu, 2013. "Delving into Liberia's energy economy: Technical change, inter-factor and inter-fuel substitution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 122-130.

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